There are various reasons for taking stock of individual objects in an environment. For example, taking stock of a wood is of great interest. For example, the knowledge of the amount of wood present, the composition of the wood of different species of tree, their spatial distribution and their age distribution are of interest from both an economic and an ecological standpoint. The chronological sequence of wood development is likewise significant for clarifying the following issues: How badly has a wood been damaged by a storm? How well has the wood recovered from a storm? Does the wood develop better or worse in the long term if pests are actively controlled or not? How much has a wood regenerated just by trees growing again?
When a wood is segmented into individual trees, a wood inventory is carried out “manually” on a selected test area by inspecting and counting the trees. This procedure is however very time-consuming and not very representative for an entire wood. Methods have therefore been developed with which the recording and evaluation of a wood takes place with flights or aided by satellites. In a possible procedure, the environment to be segmented is recorded passively in the visible or near and middle infra-red wavelength range and evaluated. Furthermore, active methods exist in which the wood is scanned with a laser scanner method. To this end, the wood is irradiated with laser beams. Signals backscattered by the trees are recorded with measurement technology and evaluated.
In the passive area by area recording of the wood with electromagnetic radiation in the visible or in the near and middle infra-red wavelength ranges, the wood surface, that is, the canopy of the wood, is recorded. This is in particular the highest points of the crowns of the trees. In contrast, the interior of the wood, in which smaller trees may be hidden, remains invisible to this method.
The conventional laser scanners which are used for segmenting the wood into individual trees are sometimes also able to scan the interior of the wood to a certain extent. In this case what are known as main pulses of the backscattered signal, which are mostly caused by the floor of the wood and by the canopy, are recorded by measurement technology. In this case, spatial coordinates of backscatter points on the tree crowns are determined from the known direction of the emitted laser beam and the transit time until receipt of the backscattered pulses. For this reason only insufficient information about the interior of the wood can be gained on the basis of such laser scanners.
These shortcomings during recording are also reflected in the subsequent evaluation process. Approaches to segmenting individual trees of a wood generally proceed from the tree canopy recorded by measurement technology. However, as described, points below the tree crowns are not taken into account thereby. Local maximums in the wood surface define the positions of the tree trunks. In Hyyppä, J., Kelle, O., Lehikoinen, M., Inkinen, M., 2001, “A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners”, IEEE Transactions on Geoscience and remote Sensing, 39:969-975, the tree canopy is for example formed from the locally highest measured points. From Solberg, S., Naesset, E., Bollandsas, O. M., 2006, “Single Tree Segmentation Using Airborne Laser Scanner Data in a Structurally Heterogeneous Spruce Forest”, Photogrammetric Engineering & Remote Sensing, Vol. 72, No. 12, December 2006, pages 1369-1378, it is known to calculate a three-dimensional area by interpolation from the highest measured points. In order to segment this three-dimensional surface into individual tree crown sections, it is assumed that each tree locally forms the highest point in the tree canopy. It is known from Vincent, L., Soille, P., 1991, “Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations”, IEEE Transactions of Pattern Analysis and Machine Intelligence, Vol. 13, No. 6, June 1991, pages 583-598 to obtain the tree crown segments as encircling polygons by means of what is known as the watershed algorithm. In contrast, Persson, A., Holmgren, J. and Söderman, U., 2002, “Detecting and measuring individual trees using an airborne laserscanner” Photogrammetric Engineering & Remote Sensing 68(9), pages 925-932 proposes determining the tree crown segments by means of a segmentation which depends on the gradient of the wood surface. A corresponding proposal can also be found in Hyyppä, J., Kelle, 0., Lehikoinen, M., Inkinen, M., 2001, “A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners”, IEEE Transactions on Geoscience and remote Sensing, 39:969-975. The publication Solberg, S., Naesset, E., Bollandsas, O. M., 2006, “Single Tree Segmentation Using Airborne Laser Scanner Data in a Structurally Heterogeneous Spruce Forest”, Photogrammetric Engineering & Remote Sensing, Vol. 72, No. 12, December 2006, pages 1369-1378 proposes the use of the region growing approach to obtain the tree crown segments. All the known methods, however, completely omit information below the wood surface, even if information is sometimes present in the backscattered signals. Only a segmentation in two-dimensional form can take place thereby, which does not allow detailed conclusions to be drawn about the wood.
In Wang, Y., Weinacker, H., Koch, B., 2007, “Development of a Procedure for Vertical Structure Analysis and 3D-Single Tree Extraction within Forests Based on Lidar Point Cloud”, Proceedings of the ISPRS Workshop Laser Scanning 2007 and SilviLaser 2007, Vol. XXXVI, PART 3/W52, 12-14 Sep. 2007, Espoo, pages 419-423, in order to be able to carry out a three-dimensional segmentation of the wood, the wood region is subdivided into different planes which lie on top of each other. In these two-dimensional planes, tree crown segments are identified by means of morphological operations from image processing. The tree crown segments are then assembled hierarchically. This procedure however only makes it possible to evaluate the three-dimensional information available from the laser signals in an indirect and thus not very consistent manner.
To irradiate a wood which is to be segmented, what are known as full waveform laser scanners are furthermore known, which can record not only the generally most strongly backscattered pulses of the wood surface and of the wood floor, but a complete backscattered chronological signal profile. It is in principle possible to record points of backscattering leaves and branches below the tree crowns as well with these laser scanners. Until now, however, no methods are known with which the data delivered by full waveform laser scanners can be evaluated in such a manner that a three-dimensional segmentation is made possible.
It is therefore the object of the present invention to specify an improved method for computer-aided segmentation of an environment into individual objects which allows three-dimensional analysis of the environment. In particular, a method for computer-aided segmentation of the wood into individual trees is to be specified. A further object of the invention consists in specifying a correspondingly configured device.
While the particular method and a device for computer-aided segmentation into individual objects as herein shown and described in detail is fully capable of attaining the above-described objects of the invention, it is to be understood that these are the presently preferred embodiments of the present invention and are thus representative of the subject matter which is broadly contemplated by the present invention, that the scope of the present invention fully encompasses other embodiments which may become obvious to those skilled in the art.
Furthermore, the described features, advantages, and characteristics of the invention may be combined in any suitable manner in one or more embodiments. One skilled in the relevant art will recognize that the invention may be practiced without one or more of the specific features or advantages of a particular embodiment. In other instances, additional features and advantages may be recognized in certain embodiments that may not be present in all embodiments of the invention. Features and advantages of the present invention will become more fully apparent from the following description and appended claims.